Optimal Maintenance Scheduling of Generators Using Multiple Swarms-MDPSO Framework
In this paper, a challenging power system problem of effectively scheduling generating units for maintenance is presented and solved. the problem of generator maintenance scheduling (GMS) is solved in order to generate optimal preventive maintenance schedules of generators that guarantee improved economic benefits and reliable operation of a power system, subject to satisfying system load demand, allowable maintenance window, and crew and resource constraints. a multiple swarm concept is introduced for the modified discrete particle swarm optimization (MDPSO) algorithm to form a robust algorithm for solving the GMS problem. This algorithm is referred to by the authors as multiple swarms-modified particle swarm optimization (MS-MDPSO). the performance and effectiveness of the MS-MDPSO algorithm in solving the GMS problem is illustrated and compared with the MDPSO algorithm on two power systems, the 21-unit test system and 49-unit Nigerian hydrothermal power system. the GMS of the two power systems are considered and the results presented shows great potential for utility application in their area control centers for effective energy management, short and long term generation scheduling, system planning and operation.
Y. Yare and G. K. Venayagamoorthy, "Optimal Maintenance Scheduling of Generators Using Multiple Swarms-MDPSO Framework," Engineeing Applications of Artificial Intelligence, Elsevier, Sep 2010.
The definitive version is available at https://doi.org/10.1016/j.engappai.2010.05.006
Electrical and Computer Engineering
National Science Foundation (U.S.)
Keywords and Phrases
Generator Maintenance; Multiple Swarms-Modified Discrete Particle Swarm Optimazation; Optimal Scheduling; Reliability Index
Article - Journal
© 2010 Elsevier, All rights reserved.
01 Sep 2010